_base_ = './base_nwpuv2.py'
# model settings
model = dict(
    type='WeakRCNN',
    # pretrained='open-mmlab://detectron2/resnet50_caffe',
#     backbone=dict(
#         type='ResNet',
#         depth=50,
#         num_stages=3,
#         strides=(1, 2, 2),
#         dilations=(1, 1, 1),
#         out_indices=(2, ),
#         frozen_stages=1,
#         norm_cfg=dict(type='BN', requires_grad=True),
#         norm_eval=True,
#         style='caffe',
#         init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),

    pretrained=None,
    backbone=dict(type='VGG16'),
    neck=None,    

    roi_head=dict(
        type='OICR_FSCE_RoIHead',
        bbox_roi_extractor=dict(
            type='SingleRoIExtractor',
            roi_layer=dict(type='RoIPool', output_size=7),
            out_channels=512,
            featmap_strides=[8]),
        bbox_head=dict(
            type='OICR_FSCE_Head',
            in_channels=512,
            hidden_channels=4096,
            roi_feat_size=7,
            num_classes=10))
)
work_dir = 'work_dirs/nwpuv2/oicr_fsce_vgg16_test/'
load_from = 'pretrain/vgg16.pth'
